De-duplicating distributed file system using cloud-based object store

ABSTRACT

Techniques to provide a de-duplicating distributed file system using a cloud-based object store are disclosed. In various embodiments, a request to store a file comprising a plurality of chunks of file data is received. A determination to store at least a subset of the plurality of chunks is made. The request is responded to at least in part by providing an indication to store two or more chunks comprising the at least a subset of the plurality of chunks comprising the file as a single stored object that includes the combined chunk data of said two or more chunks.

CROSS REFERENCE TO OTHER APPLICATIONS

This application is a continuation of co-pending U.S. patent application Ser. No. 14/675,425, entitled DE-DUPLICATING DISTRIBUTED FILE SYSTEM USING CLOUD-BASED OBJECT STORE filed Mar. 31, 2015 which is incorporated herein by reference for all purposes.

BACKGROUND OF THE INVENTION

Distributed file systems, file sharing services, etc. have been provided. In one approach, a file system client, application, and/or agent running on a client system may receive file system calls made by applications running on the client system, and may be configured to make corresponding calls to a remote file system server, e.g., a metadata server. For example, to store or update a file the file system client may generate and send to the file system metadata server a write request. The write request may identify a plurality of chunks of data desired to be written to a file. The metadata server may be configured to provide a response indicating one or more locations, e.g., in a cloud-based object store, to which the data should be written by the client.

Some file system features, such as de-duplication, may be optimized by working with chunks of data that are relatively small compared to the object size of objects that cloud-based or other object stores may be optimized to store.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments of the invention are disclosed in the following detailed description and the accompanying drawings.

FIG. 1 is a block diagram illustrating an embodiment of a distributed file system and environment.

FIG. 2 is a block diagram illustrating an embodiment of a client system.

FIG. 3 is a block diagram illustrating an embodiment of a distributed file system.

FIG. 4 is a flow chart illustrating an embodiment of a process to store a file or other file system object in a distributed file system.

FIG. 5 is a flow chart illustrating an embodiment of a process to handle a request to store a file or other file system object in a distributed file system.

FIG. 6 is a flow chart illustrating an embodiment of a process to store file segment or “chunk” data associated with a distributed file system.

FIG. 7 is a flow chart illustrating an embodiment of a process to access a file or other file system object stored in a distributed file system.

FIG. 8 is a flow chart illustrating an embodiment of a process to handle a request to access a file or other file system object stored in a distributed file system.

FIG. 9 is a block diagram illustrating an example set of file system metadata tables used in an embodiment of a distributed file system.

FIG. 10 is a block diagram illustrating an example of file segmentation at different levels of granularity in an embodiment of a distribute file system.

FIG. 11 is a flow chart illustrating an embodiment of a process to configure a distributed file system to store file data.

FIG. 12 is a block diagram illustrating an example of metadata tables used to store file data in an embodiment of a distributed file system.

FIG. 13 is a flow chart illustrating an embodiment of a process to verify distributed file system data as stored in a cloud-based object store.

FIG. 14 is a flow chart illustrating an embodiment of a process to manage file data that has been cached in connection with verifying distributed file system data as stored in a cloud-based object store.

FIG. 15 is a flow chart illustrating an embodiment of a process to determine that a stored object associated with a plurality of chunks of file data can be deleted.

DETAILED DESCRIPTION

The invention can be implemented in numerous ways, including as a process; an apparatus; a system; a composition of matter; a computer program product embodied on a computer readable storage medium; and/or a processor, such as a processor configured to execute instructions stored on and/or provided by a memory coupled to the processor. In this specification, these implementations, or any other form that the invention may take, may be referred to as techniques. In general, the order of the steps of disclosed processes may be altered within the scope of the invention. Unless stated otherwise, a component such as a processor or a memory described as being configured to perform a task may be implemented as a general component that is temporarily configured to perform the task at a given time or a specific component that is manufactured to perform the task. As used herein, the term ‘processor’ refers to one or more devices, circuits, and/or processing cores configured to process data, such as computer program instructions.

A detailed description of one or more embodiments of the invention is provided below along with accompanying figures that illustrate the principles of the invention. The invention is described in connection with such embodiments, but the invention is not limited to any embodiment. The scope of the invention is limited only by the claims and the invention encompasses numerous alternatives, modifications and equivalents. Numerous specific details are set forth in the following description in order to provide a thorough understanding of the invention. These details are provided for the purpose of example and the invention may be practiced according to the claims without some or all of these specific details. For the purpose of clarity, technical material that is known in the technical fields related to the invention has not been described in detail so that the invention is not unnecessarily obscured.

A de-duplicating distributed file system that segments files in chunks of a first size for purposes of de-duplication but stores file data in much larger objects to take advantage of the performance characteristics of typical cloud-based object stores is disclosed. In various embodiments, a file system client running on a client device segments a file to be stored into “chunks” of a first size. Data representing the chunks, such as hashes or other representations of the respective chunks, is sent to a remote file system metadata server. The server performs deduplication processing to determine which, if any, of the chunks may already be stored by the file system. For those chunks that have not yet been stored by the file system, the server responds to the client with instructions to combine a plurality of chunks in a combined object and to store the combined object, e.g., via an HTTP PUT or other request, in a cloud-based object store at a location specified by the server, e.g., using a uniform resource indicator (URI) or other locator provided by the server.

FIG. 1 is a block diagram illustrating an embodiment of a distributed file system and environment. In the example shown, the distributed file system environment 100 includes a plurality of client systems and/or devices, represented in FIG. 1 by clients 102, 104, and 106. In the example shown, the clients connect (wireless or otherwise) to a network 108, e.g., one or more of a local area network (LAN), a wide area network (WAN), the Internet, and/or one or more other public and/or private networks. The clients have access via network 108 to a file system metadata server 110. Applications on the respective clients, such as clients 102, 104, and 106, make file system calls, which result in various embodiments in corresponding remote calls being made to file system metadata server 110. For example, a file system client, agent, or other entity on the client may intercept or otherwise receive calls by the application to a local (e.g., native) file system, and may redirect such calls to an agent configured to make corresponding remote calls to file system metadata server 110 (e.g., transparently to the application).

In the example shown, data comprising objects stored in the file system, such as files, is stored in a cloud-based object store 112. In some embodiments, files may be segmented into a plurality of segments or “chunks”, each of which is stored in a corresponding location in the cloud-based object store. File system calls are made to file system metadata server 110, which stores file system metadata in a file system metadata storage 114, e.g., in a database or other data store. File system metadata server 110 may store in file system metadata store 114, for example, a segment or “chunk” map for each file or other object stored and represented in the file system. For example, for each file name (e.g., pathname) the file system metadata server 110 may store in a corresponding segment map a hash or other representation of each segment, and for each a corresponding location in which the segment is (or is to be) stored in cloud-based object store 112. Other file system metadata, such as metadata typically stored by a file system, may be stored by file system metadata server 110 in file system metadata store 114. Examples include, without limitation, a directory, file, or other node/object name; an identification of parent and/or child nodes; a creation time; a user that created and/or owns the object; a time last modified and/or other time; an end-of-file (EOF) or other value indicative of object size; security attributes such as a classification, access control list, etc.; and/or other file system metadata.

While in the example shown in FIG. 1 the file system metadata server 110 and the cloud-based object store 112 are shown as separate systems, located in different networks and/or physical locations, in other embodiments the file system metadata and file system content data may be stored together, e.g., both on cloud-based resources and/or both on enterprise or other network servers, etc.

FIG. 2 is a block diagram illustrating an embodiment of a client system. In the example shown, the client system/device 102 of FIG. 1 is shown to include an application 202 running in an environment provided by an operating system 204. The operating system 204 includes a kernel (not shown) and other components configured to provide services and/or functionality to applications such as application 202. For example, operating system 204 may include and/or be configured to provide access to a native file system (not shown) of client system 102. Application 202 may be configured to make file system calls to the native file system, e.g., to store files or other objects created by/using application 202, to modify, move, or delete such objects, etc. In the example shown, file system calls made by application 202, represented in FIG. 2 by the downward pointing arrow originating in the block labeled “app” (202), are intercepted by a kernel module (or other component) 206 and redirected to a file system client (or other file system agent) 208. In some embodiments, file system agent 208 comprises a client application running in user space. In some embodiments, file system agent 208 comprises a kernel or other operating system component or module. File system client 208 in this example has associated therewith a local cache 210. In various embodiment, cache 210 may be used to buffer and/or otherwise stage file data prior to its being sent to remote storage (e.g., cloud-based object store 112 of FIG. 1), and/or to facilitate access to data stored previously but to which access may be requested later.

The client system 102 includes a network communication interface 212 that provides network connectivity, e.g., to a network such as network 108 of FIG. 1. For example, a request from app 202 to access a file stored remotely in various embodiments may result in file system client 208 making a remote call, via network communication interface 212, for example to a file system metadata server such as server 110 of FIG. 1.

In various embodiments, file system client 208 may be configured to store in a metadata write buffer comprising or otherwise associated with file system client 208 and/or cache 210 one or more file system operations and/or requests affecting file system metadata comprising a portion of the file system metadata with respect to which a file system metadata write lease is held by file system client 208. For example, file system operations affecting metadata may be buffered as received, e.g., as a result of local file system calls by applications such as application 202 of FIG. 2, and may be communicated to the remote file system metadata server asynchronously and/or upon occurrence of an event, e.g., receipt of an indication that a metadata write lease “break” event has been received and/or has occurred. For example, a second client system may indicate a desire and need to perform operations affecting a portion of the file system metadata with respect to which a first client system holds a lease, result in a “break” communication being sent to the first client system, which in turns “flushes” at least those operations in the buffer that affect the portion of metadata with respect to which the lease had been held.

FIG. 3 is a block diagram illustrating an embodiment of a distributed file system. In the example shown, client 102 communicates via a secure session-based connection 302 with file system metadata server 110. In addition, client 102 communicates with cloud-based object store 112 via a TCP/IP or other connection that enables client 102 to store objects (e.g., file segments or “chunks”) via HTTP “PUT” requests and to retrieve segments (“chunks”) via HTTP “GET” requests. In various embodiments, client 102 (e.g., a file system client or other agent running on client 102) sends and receives distributed file system “control plane” communications via secure connection 302 (e.g., file system operations that change or require the processing and/or use of file system metadata), whereas communicates sent via connection 304 may be considered to comprising a “data plane” via which file system object data (i.e., segments or “chunks”) may be stored and/or retrieved. In the example shown, file system metadata server 110 has access to active directory 306, which in various embodiments may comprise information usable to authenticate users of clients such as client 102.

In various embodiments, file system objects, such as files, may be stored by a client on which a distribute file system client or other agent has been installed. Upon receiving a request to store (or modify) a file system object, in various embodiments the file system client segments the object into one or more segments or “chunks” and computes a reference (e.g., a hash) for each. The references are included in a file system request sent to the file system metadata server, e.g., via a secure connection such as connection 302 of FIG. 3. The file system metadata server returns information to be used by the file system client to store (non-duplicate) segments/chunks in the cloud-based object store by sending the segment data directly to the cloud-based object store, e.g., via PUT requests sent via a connection such as connection 304 of FIG. 3.

FIG. 4 is a flow chart illustrating an embodiment of a process to store a file or other file system object in a distributed file system. In various embodiments, the process of FIG. 4 may be performed on a client system or device, e.g., by a file system client or other agent running on the client system/device, such as file system client 208 of FIG. 2. In the example shown, a request is received, e.g., from an application, to store a file (402). The file is segmented into one or more segments (404). For each segment, a segment reference, e.g., a hash, is computed (406). A file write request that includes the segment references is sent to the file system metadata server (408). A set of uniform resource indicators (URI's) or other pointers is received from the file system metadata server (410). In various embodiments, the set of pointers may include pointers only for those segments not already stored by the distributed file system. The received pointers are used to store segments, e.g., via HTTP “PUT” requests sent directly to the cloud-based object store (412).

FIG. 5 is a flow chart illustrating an embodiment of a process to handle a request to store a file or other file system object in a distributed file system. In various embodiments, the process of FIG. 5 may be performed by a file system metadata server, such as file system metadata server 110 of FIG. 1. In the example shown, a request to store a file is received (502). A segment (“chunk”) map that associates the file system object name and/or other identifier (e.g., file name, pathname) with a set of one or more segment references (e.g., hash values) is created (504). Segments that are not duplicates of segments already stored by the distributed file system are identified, for example based on the segment references (506). For each segment that is not a duplicate, a storage location is computed (e.g., based at least in part on all or part of the segment reference) and a URI or other pointer usable to store the segment directly in the cloud-based data store is generated (508). In various embodiments, the URI or other pointer is signed cryptographically by the file system metadata server. The URI may have an expiration time by which it must be used to store the segment. The URI's are sent to the file system client from which the request to store the file was received (510).

FIG. 6 is a flow chart illustrating an embodiment of a process to store file segment or “chunk” data associated with a distributed file system. In various embodiments, the process of FIG. 6 may be performed by a cloud-based object store, such as object store 112 of FIG. 1. In the example shown, a “PUT” request associated with a URI specified in the request is received (602). A cryptographic signature associated with the URI and an expiration time encoded in the URI are checked (604). For example, the cloud-based object store may be provisioned to check that the URI has been signed by a trusted file system metadata server and/or that an expiration time of the URI has not elapsed. If the URI is determined to be currently valid (606), a payload data associated with the PUT request, e.g., file system object segment or “chunk” data, is stored in a location associated with the URI (608). If the URI is determined to not be valid (606), the PUT request fails (610), and the file system client receives a response indicating it must obtain a new URI from the file system metadata server.

In various embodiments, file system objects, such as files, may be retrieved by a client on which a distribute file system client or other agent has been installed. Upon receiving a request to access a file system object, in various embodiments the file system client sends a file access request to the file system metadata server, e.g., via a secure connection such as connection 302 of FIG. 3. The file system metadata server returns information (e.g., one or more URI's or other pointers) to be used by the file system client to retrieve segments/chunks directly from the cloud-based object store, e.g., via GET requests sent via a connection such as connection 304 of FIG. 3.

FIG. 7 is a flow chart illustrating an embodiment of a process to access a file or other file system object stored in a distributed file system. In various embodiments, the process of FIG. 4 may be performed on a client system or device, e.g., by a file system client or other agent running on the client system/device, such as file system client 208 of FIG. 2. In the example shown, a request to access a file system object, e.g. a file identified by file name, is received from an application (702). A request is sent to a file system metadata server to retrieve the file (704). A set of segment references, and for each a corresponding URI and encryption key, is received from the file system metadata server (706). A local cache is checked to determine whether any required segments are present in the cache (708). For all segments not present in the cache, the associated URI is used to send a GET request to retrieve the segment from the cloud-based object store, and the associated key is used to decrypt the segment once it has been received from the object store in encrypted form (710). The segments are used to reconstruct the file and provide access to the file to the application from which the access request was received (712).

FIG. 8 is a flow chart illustrating an embodiment of a process to handle a request to access a file or other file system object stored in a distributed file system. In various embodiments, the process of FIG. 5 may be performed by a file system metadata server, such as file system metadata server 110 of FIG. 1. In the example shown, a request to access a named file is received (802). A segment map associated with the file is retrieved and used to determine a set of segment references (e.g., hashes), and for each a corresponding URI indicating where the segment is stored in the cloud-based segment store and an encryption key usable to decrypt the segment (804). The segment references, URI's, and keys are returned to the file system client from which the file access request was received (806).

FIG. 9 is a block diagram illustrating an example set of file system metadata tables used in an embodiment of a distributed file system. In various embodiments, the tables 902, 904, and 906 of FIG. 9 may be created and maintained by a file system metadata server, such as file system metadata server 110 of FIGS. 1 and 3. In the example shown, an inode table 902 is used to store data associating each named file system object, e.g., directories, files, or other objects, with a corresponding inode or other unique number or identifier. Chunk map table 904 is used in various embodiments to store for each file, and for each of one or more segments (chunks) into which that file has been broken up to be stored, an offset of the chunk within the file, a chunk identifier (chunk id), and other metadata. For example, a file that has been stored as three chunks would have three entries (rows) in table 904, one for each chunk. In various embodiments, the chunk id is a monotonically increasing value, with each successively stored chunk being given a next chunk id in alphanumeric order. In various embodiments, chunks are immutable once stored. If file data is modified, affected data is stored as a new chunk and assigned a next chunk id in order. As a result, a chunk with a higher chunk id by definition was stored subsequent to a chunk with a lower chunk id, and it can be assumed neither was modified since it was created and stored.

Referring further to FIG. 9, the chunk metadata table 906 includes a row for each chunk, identified by chunk id (column 908 in the example shown), and for each chunk metadata indicating the size of the chunk; other metadata; a reference count (column 910) indicating how many currently live files (or other file system objects) reference the chunk; and metadata indicating a state of the chunk, i.e., whether it has been verified or deleted (column 912).

In various embodiments, when a chunk is first stored the chunk is considered to be initially in an “unverified” state, and metadata reflecting the unverified state of the chunk may be stored initially in column 912 of table 906. Verification may be performed by the file system metadata server and may include reading the chunk as stored in the cloud-based object store, verifying that the chunk data corresponds to what the file system expects (e.g., computing a hash of the chunk as read by the server and comparing the hash to a previously-stored hash of the chunk, e.g., one received from the file system client that stored the chunk), and updating the state metadata 912 in table 906 to reflect a “verified” state for the chunk once it has been verified.

A de-duplicating distributed file system that segments files in chunks of a first size for purposes of de-duplication but stores file data in much larger objects to take advantage of the performance characteristics of typical cloud-based object stores is disclosed. In various embodiments, a file system client running on a client device segments a file to be stored into “chunks” of a first size. Data representing the chunks, such as hashes or other representations of the respective chunks, is sent to a remote file system metadata server. The server performs de-duplication processing to determine which, if any, of the chunks may already be stored by the file system. For those chunks that have not yet been stored by the file system, the server responds to the client with instructions to combine a plurality of chunks in a combined object and to store the combined object, e.g., via an HTTP PUT or other request, in a cloud-based object store at a location specified by the server, e.g., using a uniform resource indicator (URI) or other locator provided by the server.

FIG. 10 is a block diagram illustrating an example of file segmentation at different levels of granularity in an embodiment of a distribute file system. In the example shown, a first file 1002 includes the data shown, in this example the data “A B C D E F”. A second file 1004, stored subsequent to the first file being stored, includes the data “C D A B E G”, with the capitals letters in the respective files 1002 and 1004 representing in each file the same sequence of bytes of data, e.g., “A” at the beginning of first file 1002 is the same data as the data represented by the same capital letter “A” in the second file 1004

In FIG. 10, two possible segment or “chunk” sizes that could be used, for purposes of de-duplication, for example, are shown. In the first example, chunks 1006 each of a size corresponding to three of the capital letters representing data comprising the files 1002 and 1004, respectively, are shown. In this example, segmenting the files 1002 and 1004 into chunks 1006 of the size shown would result in no duplicate chunks being found as between the first file 1002 and the second file 1004. By comparison, a set of chunks 1008 created by segmenting the files 1002 and 1004 at a finer granularity (i.e., smaller chunk size) would result in significantly improved de-duplication. In this example, a chunk 1014 of file 1004 would be determined to be a duplicate of previously-stored chunk 1012 of file 1002, and chunk 1018 of file 1004 would be determined to be a duplicate of previously-stored chunk 1016 of file 1002. In this example, chunk 1022 of file 1004 would not be determined to be a duplicate of any previously-stored chunk of file 1002, in this case due to difference between chunk 1022 of file 1004 and chunk 1020 of file 1002 (and the other chunks of file 1002). In the example shown, an even further degree of de-duplication could be achieved by segmenting the files into chunks of a size corresponding to individual capital letters as represented in FIG. 10, because if chunks of that size were used only the chunk corresponding to capital letter “G” if file 1004 would be found to not be a duplicate of any chunk in file 1002.

The example in FIG. 10 illustrates that in general chunks of a smaller size may yield higher de-duplication benefits than chunks of a larger size. However, if chunks that are too small are used, the overhead associated with computing and storing hashes of chunk data to detect duplicates, etc., may become too costly. Therefore, typically a balance is struck between achieving more benefit of de-duplication through relatively smaller chunk size, and the overhead associated with processing the chunks.

In various embodiments of a distributed file, a further consideration is the efficiency of storing chunks in a cloud-based object stored, such as cloud-based object store 112 of FIG. 1. Typically, such cloud-based object stores are optimized to store objects that are very large relative to the chunk size that may be optimal for purposes of de-duplication and related overhead. For example, for a typical cloud-based object store, the latency and other overhead associated with storing an object may increase linearly with size up to a certain size, but then level off for objects beyond a certain size, e.g., a size that is relatively large compared to a chunk size that may be optimal for other purposes, such as de-duplication. To take advantage of this characteristic, in various embodiments or a distribute file system as disclosed herein files are segmented for purposes of file system operations into a chunk size that is advantageous for purposes of de-duplication and/or other file system processing, but file data is stored in cloud-based object store(s) such as object store 112 of FIG. 1 in objects (sometimes referred to herein as “blobs”, to distinguish them clearly from “files” or “chunks”) that are relatively much larger in size than the chunk size. In various embodiments, a file system client may be configured and/or instructed to combine chunks into a larger combined object, and then to store the combined object (or “blob”) in a cloud-based object store.

FIG. 11 is a flow chart illustrating an embodiment of a process to configure a distributed file system to store file data. In various embodiments, the process of FIG. 11 may be used to develop and configure distributed file system components, such as file system client 208 of FIG. 2 and file system metadata server 104 of FIGS. 1 and/or 6. In the example shown, a chunk size to achieve a desired performance with respect to de-duplication and/or one or more other file system objectives is determined (1102). In various embodiments, the determination may be made in whole or in part based on domain knowledge, static analysis of all or part of a set of files, observed de-duplication performance in test performed using chunks of different sizes, etc. An object or “blob” size to be used to store file system data in a manner that takes advantage of object size-related characteristics of a cloud-based or other object store is determined (1104). For example, a performance graph or other representation of object store performance and/or costs (e.g., latency, overhead) by object size may be generated and used to select an object (“blob”) size that achieves a desired level of performance by the object store. The distribute file system is configured to segment files into chunks of the determined chunk size for purposes of file system operations (e.g., de-duplication), and to combine multiple chunks into larger objects (“blobs”) of the determined object size (1106) for storage in a cloud-based object store.

In some embodiments, the number of chunks that may be combined to former a larger object (“blob”) to be stored in a cloud-based object store may be variable. For example, the number of chunks may vary based on the size of a file or set of files being stored. In some embodiments, the file system client may be configured to determine the number of chunks to be combined to form a larger object to be stored in a cloud-based object store. In some embodiments, the determination as to the number of chunks to be combined and/or which chunks are to be included in which object (“blob”) may be made at a file system server, such as file system metadata server 104 of FIGS. 1 and/or 6. In some embodiments, the file system client may be configured to receive an indication from the server as which chunks are to be combined in which object, and to create and store objects based on such instructions.

In some embodiments, chunks associated with two or more different files may be included in a same object to be stored in a cloud-based object store. In some embodiments, chunks associated with files associated with two or more different file system clients may be included in an object as stored in a cloud-based object store. For example, in some embodiments, de-duplication may be performed across file system clients, which in some circumstance may result in one or more chunks comprising a stored object (“blob”) being referenced by files associated with different file system clients.

FIG. 12 is a block diagram illustrating an example of metadata tables used to store file data in an embodiment of a distributed file system. In various embodiments, metadata tables such as tables 1202 and 1210 of FIG. 12 may be created and maintained by a distributed file system metadata server, such as file system metadata server 104 of FIGS. 1 and/or 6. In the example shown, a chunk metadata table 1202 includes a chunk identifier column 1203 in which a monotonically increasing chunk identifier is stored; a chunk hash column 1204 in which for each chunk a corresponding hash computed based on all or part of the chunk's data is stored. For each chunk, a “blob id” that identifies a larger stored object (“blob”) in which the chunk data was included is listed in a “blob id” column 1206. A location of each chunk within the corresponding stored object (“blob”) within which it is included is listed in an “offset” column 1208. For a given chunk, then, table 1202 may be used to find the stored object within which the chunk's data is included as stored, e.g., in a cloud-based object store, and an offset within that object indicating where the chunk's data is located within the object's data.

As indicated by the arrow shown between the blob id value of “1” in the first, second, and fourth rows of table 1202 to the entry (row) associated with the same blob id “1” in blob metadata table 1210, the blob id as stored in chunk metadata hash table 1202 for a given chunk hash value may be used to locate in blob metadata table 1210 a corresponding entry (see blob id column 1212) that includes blob metadata such as an encryption key or other secret data used to encrypted data comprising the blob (blob encryption key column 1214), a location in which the blob is stored, e.g., in a cloud-based object store (URI column 1216), and an indication of a number of chunks associated with file system objects that are currently live and/or otherwise subject to being retained (chunks referencing count column 1218). As to the latter column, for example, in the entry (row) for blob id=1, the corresponding value in chunks referencing count column 1218 indicates that 3 chunks that are currently live (or otherwise subject to being retained, e.g., by virtue of being associated with a snapshot that remains stored) reference that blob. In various embodiments, as described more fully below in connection with FIG. 15, the chunks referencing count column may be used to determine when a blob comprising a plurality of chunks may be subject to being deleted, e.g., from a cloud-based object store in which the blob is stored.

In various embodiments, verification of file system data stored as disclosed herein is performed by the file system, e.g., by a file system metadata server, such as file system metadata server 104 of FIGS. 1 and/or 6. In various embodiments, verification enables a guarantee of corruption-free de-duplicated storage of file system objects to be provided across clients, even in the presence of misconfigured and/or malfunctioning (e.g., “buggy”) or malicious clients.

In some embodiments, a stored object (“blob”) comprising a plurality of chunks for file data is retrieved from a cloud-based object store. The retrieved object may be stored locally, e.g., in a cache, and used to verify component chunks comprising the object. Various techniques may be used to determine how long a cached copy of a given object (“blob”) should remain in the cache to facilitate verification.

FIG. 13 is a flow chart illustrating an embodiment of a process to verify distributed file system data as stored in a cloud-based object store. In various embodiments, the process of FIG. 13 may be used by a distributed file system metadata server, such as file system metadata server 104 of FIGS. 1 and/or 6, to verify file system data as stored. In the example shown, processing begins with or advances to a next chunk to be verified (1302). For example, the file system metadata server verification process or module may pull a next chunk verification task from a verification queue. As chunks are reported by file system clients as having been stored in the cloud-based object store, e.g., corresponding verification tasks may be added to a verification queue. In some embodiments, the verification queue may comprise a database table or other data structure in which data identifying chunks to be verified may be stored. Referring further to FIG. 13, a “blob” or other stored object identifier associated with a stored object in which data comprising the chunk is included is determined (1304), e.g., by performing a lookup in a chunk hash table such as table 1202 of FIG. 12. If the blob is not already present in a local cache, e.g., cache 210 of FIG. 2 (1306), the blob is retrieved from the cloud-based object store, e.g., using data from a blob metadata table such as table 1210 of FIG. 12, and stored in the cache (1308). If the blob is already present in a local cache (1306), or if not once the blob has been obtained and stored in the cache (1308), the cached copy of the blob is used to obtain the data corresponding to the chunk, e.g., using offset of the chunk within the blob as indicated in the corresponding entry in the chunk hash table, and the chunk data is used to verify the chunk (1310). For example, a hash of the chunk data as stored in the blob may be compared to a hash for the chunk as stored in the chunk metadata. The process of FIG. 13 is repeated through successive iterations so long as there are chunks to be verified (1312).

In various embodiments, techniques may be used to determine how long to continue to cache a blob that has been retrieved to perform verification processing, e.g., as in FIG. 13.

FIG. 14 is a flow chart illustrating an embodiment of a process to manage file data that has been cached in connection with verifying distributed file system data as stored in a cloud-based object store. In various embodiments, the process of FIG. 14 may be used by a distributed file system metadata server, such as file system metadata server 104 of FIGS. 1 and/or 6, to determine how long to cache file system data that has been read from a cloud-based object store. In the example shown, for each blob that is cached, a count of the chunks associated with that blob that still have to be verified is maintained (1402). For example, when a blob is retrieved to perform verification, as in step 1308 of FIG. 13, in some embodiments the verification queue and the chunk hash table, which maps chunks to blob id's, may be used to determine how many chunks comprising the blob are in the verification queue. In some embodiments, each time a chunk is verified the “chunks remaining to be verified” count for the associated cached blob is decremented. If the count is decremented to equal “0” (1404), indicating in some embodiments that no further chunks comprising the blob remain to be verified, the blob is marked as being “okay” to remove from the cache (1406). Otherwise, the blob continues to be stored in the cache (1408), e.g., to ensure it will be available from the cache to obtain the chunk data to verify one or more chunks comprising the blob that have yet to be verified. In some embodiments, other cache policies may result in a blob being retained for a time after the “chunks remaining to be verified” count has been decremented to zero, and in some embodiments a blob may be removed from the cache based on a policy other than because the count has been decremented to zero. For example, in various embodiments time, space availability, and other considerations may result in a blob being removed from the cache despite there being one or more chunks comprising that blob that remain to be verified.

In various embodiments, combining a plurality of chunks to form a larger object (“blob”) to store in a cloud-based object store results in a need to be able to determine that no chunk comprising a blob is needed any longer, so that the storage location in which the blob is stored can be reused, e.g., through a process of “garbage collection”. In some embodiments, a reference count is stored for each chunk, to determine when a chunk is no longer referenced, and a separate blob-level reference count is kept for each blob, to know when the last chunk comprising the blob has become subject to being deleted.

FIG. 15 is a flow chart illustrating an embodiment of a process to determine that a stored object associated with a plurality of chunks of file data can be deleted. In various embodiments, the process of FIG. 15 may be used by a distributed file system metadata server, such as file system metadata server 104 of FIGS. 1 and/or 6, to determine that file system data as stored on a cloud-based object store may be deleted. In the example shown, an indication is received that a chunk is no longer needed and may be deleted (1502). For example, in various embodiments, the chunk's reference count may have been decremented to zero and a determination made that no snapshot that is still being retained includes the chunk. The blob in which the chunk is stored is determined, and an associated blob reference count (e.g., column 1218 of the table 1210 of FIG. 12) is decremented (1504). If the blob reference count once decremented is equal to zero (1506), the blob is marked for deletion (e.g., made subject to being garbage collected) (1508). If blob reference count as decremented is still greater than zero (1506), the process of FIG. 15 ends without marking the blob for deletion.

In various embodiments, techniques disclosed herein may enable file system operations, such as de-duplication, to be performed using a first size/granularity, i.e., a “chunk” size as described herein, while storing file system data using a stored object size (“blob” size) that takes advantage of the characteristics of a typical cloud-based object store.

Although the foregoing embodiments have been described in some detail for purposes of clarity of understanding, the invention is not limited to the details provided. There are many alternative ways of implementing the invention. The disclosed embodiments are illustrative and not restrictive. 

What is claimed is:
 1. A method of storing file system data, comprising: determining, by a processor, a deduplication chunk size for a plurality of chunks of file data associated with a file, wherein the deduplication chunk size facilitates achieving a desired deduplication performance when storing the plurality of chunks of file data, and wherein the deduplication chunk size is larger than a chunk size of a chunk included in the plurality of chunks; selecting, by the processor, which chunks of the plurality of chunks of file data to combine into a single stored object that satisfies the deduplication chunk size associated with the desired deduplication performance; combining, by the processor, the selected chunks of the plurality of chunks of file data into the single stored object satisfying the deduplication chunk size; and providing, by the processor, the single stored object that includes the combined selected chunks of the plurality of chunks of file data to remote storage.
 2. The method of claim 1, further comprising receiving a request to store the file comprising the plurality of chunks of file data, wherein the request is received from a file system client.
 3. The method of claim 2, wherein the request includes a hash or other representation of the chunks comprising the file.
 4. The method of claim 3, wherein the hash or other representation is used to determine whether a chunk comprising the file has already been stored.
 5. The method of claim 4, further comprising determining to store the plurality of chunks using the respective hash or other representation of the chunks comprising the plurality of chunks to determine that said chunks have not yet been stored.
 6. The method of claim 1, further comprising responding to the request at least in part by providing an indication to store two or more chunks comprising the plurality of chunks comprising the file as the single stored object, wherein said indication includes a locator or other identifier associated with the single stored object and data associating said plurality of chunks comprising the file with the locator or other identifier.
 7. The method of claim 6, wherein the locator or other identifier indicates a location to which the single stored object should be sent to be stored.
 8. The method of claim 2, wherein the file system client is configured to respond to said response to the request by assembling the single stored object using two or more of the plurality of chunks.
 9. The method of claim 1, further comprising storing metadata that associates said combined selected chunks with said single stored object.
 10. The method of claim 9, wherein said metadata includes for each chunk a location of data comprising that chunk with the single stored object.
 11. The method of claim 1, further comprising verifying storage of said combined selected chunks at least in part by retrieving said single stored object and using chunk data of the respective chunks comprising the single stored object to verify the chunk data as stored corresponds to the chunk data that was expected to be stored.
 12. The method of claim 1, wherein the deduplication chunk size is determined based at least in part on an overhead associated with computing and storing hashes associated with the plurality of chunks.
 13. The method of claim 1, further comprising storing for the single stored object a reference count that reflects a number of chunks comprising a blob that remain subject to being retained by a file system.
 14. The method of claim 13, further comprising decrementing the reference count based at least in part on a determination that a chunk comprising the blob no longer remains subject to being retained by a file system.
 15. A system to store file system data, comprising: a communication interface; and a processor coupled to the communication interface and configured to: determine a deduplication chunk size for a plurality of chunks of file data associated with a file, wherein the deduplication chunk size facilitates achieving a desired deduplication performance when storing the plurality of chunks of file data, and wherein the deduplication chunk size is larger than a chunk size of a chunk included in the plurality of chunks; select which chunks of the plurality of chunks of file data to combine into a single stored object that satisfies the deduplication chunk size associated with the desired deduplication performance; combine the selected chunks of the plurality of chunks of file data into the single stored object satisfying the deduplication chunk size; and provide the single stored object that includes the combined selected chunks of the plurality of chunks of file data to remote storage.
 16. The system of claim 15, wherein the processor is further configured to receive a request to store the file comprising the plurality of chunks of file data, wherein the request includes a hash or other representation of the chunks comprising the file.
 17. The system of claim 16, wherein the hash or other representation is used to determine whether a chunk comprising the file has already been stored.
 18. The system of claim 17, wherein the processor is further configured to determine to store the plurality of chunks using the respective hash or other representation of the chunks comprising the plurality of chunks to determine that said chunks have not yet been stored.
 19. The system of claim 15, wherein the processor is further configured to verify storage of said combined selected chunks at least in part by retrieving said single stored object and using chunk data of the respective chunks comprising the single stored object to verify the chunk data as stored corresponds to the chunk data that was expected to be stored.
 20. A computer program product to store file system data, the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for: determining a deduplication chunk size for a plurality of chunks of file data associated with a file, wherein the deduplication chunk size facilitates achieving a desired deduplication performance when storing the plurality of chunks of file data, and wherein the deduplication chunk size is larger than a chunk size of a chunk included in the plurality of chunks; selecting which chunks of the plurality of chunks of file data to combine into a single stored object that satisfies the deduplication chunk size associated with the desired deduplication performance; combining the selected chunks of the plurality of chunks of file data into the single stored object satisfying the deduplication chunk size; and providing the single stored object that includes the combined selected chunks of the plurality of chunks of file data to remote storage. 